This week, I’m going to discuss a very important concept to those of us who spend a lot of time recreating in the great outdoors – the difference between weather and climate. Despite what you might think, the two are not interchangeable terms, and though related, refer to different things. What exactly is the difference between weather and climate, and how are forecasts for each made?
“Weather” describes conditions in the earth’s atmosphere in a specific location over a short period of time. “Climate” refers to atmospheric behavior over a longer chunk of time. NOAA offers a very succinct way to think of the difference between the two – “climate is what you expect, weather is what you get.”
Comparing seasons from year to year is an example of examination of climate, whereas looking at individual events like sunny days, thunderstorms, rainfall, etc. is an examples of investigating weather. The lack of snowy weather in Tahoe this winter is adding up to the point where it would be a valid conclusion to state that the climate (at least on the scale of one winter) is warmer and dryer than average.
It doesn’t take a rocket scientist to realize that this winter here in Tahoe has been a funky one. If last year was the deepest winter we’ve had in 50 years, well then this year is the clear opposite. Low-tide conditions have persisted through our region straight through mid-February. Some of my esteemed colleagues here at Unofficial Networks have investigated the unusual winter weather in earlier posts – Zeb Blais visited our local NOAA offices in Reno, Charlie Cohn explained the bad winter, and Miles Clark addressed the low snowpack in the CA Sierra.
Where do our weather forecasts come from, if not from furry rodents in Pennsylvania? Most of the government-provided forecasting in the USA comes from NOAA’s staff scientists reading and interpreting various computer-based atmospheric models, and generating various forecast products based on their interpretations. These models use a suite of thermodynamic equations that are adapted to predict atmospheric conditions in specific parts of the earth’s atmosphere called ”blocks.” Daily physical observations of actual atmospheric conditions made in synchronicity by meteorologists are fed into the various models, and enhance their reliability and predictive abilities.
The US is unique in that we freely disseminate the results of our weather forecast models to the public, which has allowed a cottage industry of private-sector weather forecasting outfits, such as the Weather Channel, the Weather Underground, etc. NOAA’s partners across the pond in Europe copyright the results of their models, and thus do not share them with anyone outside of other members of the World Meteorological Orgazniation.
NOAA largely bases their forecast and weather products on their own computer weather forecast models, the GFS, or Global Forecast System, and the NAM, or North American Meso. If you are a student of the NOAA “Forecast Discussion” like I am (the ALL CAPS text-only weather discussion NOAA issues 4x daily) then you occasionally catch references to these US models, and sometimes to some of their international counterparts like the European ECWMF or European Centre for Medium-Range Weather Forecasts.
The major American-based model is the GFS, or Global Forecast System. This model is run by NOAA four times a day, predicting atmospheric conditions 16 days in advance (i.e it is predicting weather, NOT climate!). The first run of the GFS issues predictions for temperature, wind, humidity, precipitation and other conditions within blocks of Earth that are roughly 0.5 x 0.5 degrees of latitude (about 70 miles) square. Vertical forecast blocks are divided into 64 slices of the atmosphere in a “sigma pressure hybrid coordinate system.” In layman’s terms, each “slice” is an unequal part of a column of the earth’s atmosphere above each forecast block where the lowest slice is taken to be at 1000 hPa (roughly sea level), 15 slices are below 800 hPa (~6,000 ft), and 24 levels are above 100 hPa (~51,000 ft), with the highest slice at 0.3 hPa (~115,000 feet, or the edge of space).
Aside from the GFS, NOAA forecasters also make use of the NAM (North American Meso) model output by the National Centers for Environmental Prediction. The NAM runs out to 84 hours at a 12 km x 12 km horizontal resolution, which is about ⅙ the size of the GFS. Each model is used by forecasters for different purposes, and they call upon them in their forecasts to confirm or deny predictions of things like snow events, or dry spells. More often than not, the models disagree more than a few days out, and each forecaster develops a bias for one versus another. When places like the US West coast experience a change from a dry, mild weather pattern to a cold, wet on, the models often diverge in their longer-range forecasts, but then come together as the storm train nears. This is when the NOAA forecasters say things like “the storm door is ajar” and “Tahoe is about to experience a snowstorm on near Biblical proportions.”
Ensemble Forecasts such as the GEFS (Global Ensemble Forecast System) and then NAEFS (North American Ensemble Forecast System) are also utilized by NOAA and the NWS. The NAEFS is a collaborative effort between the US, Canda, and Mexico to provide high-resolution forecasts in the 1-2 week range of higher quality than what each country’s model produces on it’s own. NOAA forecasters often cite these ensemble models when they dive into the nebulous “art” of longer range (more than a few weeks) forecasting.
Most users discount the GFS’ results after 10 days, and only pay serious attention to it’s predictions out to 7 days. Why is that? The simple answer is that the atmosphere is chaotic, and highly unpredictable. At a point great er than about 2 weeks out, most reputable forecasters stop trying to forecast weather, and instead focus their efforts on predicting what the climate will be like – will temperatures be warmer than average, or will it be wetter or dryer than average? Other than observing teleconnections and other large (meso) scale weather phenomenon such as temperature and pressure, serious scientists leave long-range forecasting alone beyond the vague predictions of “temperature” and “precipitation” done for the next three months by NOAA’s CPC.
A term often cited in discussion of climate forecasting is “teleconnections,” referring to noticeable irregularities in climate (not weather!) being observed thousands of miles from the observer. Examples include the Arctic Oscillation, which describes the see-saw of sea level pressure above latitude 20 N that influences the climate of the US East Coast and Western Europe, or the Southern Oscillation, which is the atmospheric pressure component of El Nino consisting of the teleconnection between sea-level pressure in Tahiti and that in Darwin, Australia.
No discussion of long-range weather forecasting would be complete though without briefly touching upon Edward Lorenz and the “Butterfly Effect.” In 1961, when studying weather with a mathematical model, Lorenz got lazy and entered 0.506 instead of 0.506127 as a parameter into his computer. The end results were completely different in each case, leading Lorenz and colleagues to eventually posit that the simple act of a butterfly flapping its wings in Brazil could theoretically be responsible for altering the path of a tornado in Texas.
Weather and atmospheric physics are inherently complex and chaotic systems that humans are far from understanding to a level where we can make accurate predictions of weather more than a few weeks into the future. As computational power increases exposnentially, and the cost of supercomputing comes down (see Moore’s law), long-range forecasting might transition from the realm of science fiction to that of actual science.
As far as climate change forecasting is concerned, only time will tell whether the numerous predictions of the long-term climate of Earth will come true. I can tell you this though, in Tahoe in 2012 – it sure seems like things are warming up. If you asked a resident of Cordova, Alaska, though, they might disagree with you completely – it all depends upon your perspective. To this former scientist, the climate-change jury is still out, but early indications are that the climate is becoming more wildly variable than it has since we started taking careful records.